Research and application of wireless rechargeable sensor networks

Aiming to address the issue of excessive charging path length for the mobile charging trolley in wireless rechargeable sensor networks, which can lead to sensor node failure due to insufficient timely charging and consequently shorten the network's service life, we propose a method based on the Improved Ant Colony Algorithm (IACA). This method leverages the principle that ants searching for food naturally tend to find the shortest path, thereby determining the optimal shortest charging path for the mobile charging trolley. By doing so, we aim to enhance the service life of the wireless rechargeable sensor network. Simulation results demonstrate that the algorithm employed in this study achieves a 7.5% reduction in the charging path distance traveled by the mobile charging cart, a 5% decrease in the node mortality rate, and the charging efficiency has been improved by about 10% and the node charging waiting time has been reduced by about 12% and an overall extension of the network's lifetime.